Statistics
Canada
Agriculture Division
Agriculture and Rural Working Paper Series
Working Paper No. 47
Distribution and Concentration
of Canadian Livestock
Prepared by
Martin S. Beaulieu, MSc, Analyst
Analysis and Development Section
[email protected]
Frédéric Bédard, MSc, Geomatics Specialist
Spatial Analysis and Geomatics Application
[email protected]
Pierre Lanciault, PhD, Research Scientist
Formerly with Spatial Analysis and Geomatics Application
Statistics Canada, Agriculture Division
Jean Talon Building, 12th floor
Tunney’s Pasture
Ottawa, Ontario K1A 0T6
April 2001
The responsibility of the analysis and interpretation of the results is that of the authors and not of
Statistics Canada.
Statistics
Canada
Agriculture Division
Agriculture and Rural Working Paper Series
Working Paper No. 47
Distribution and Concentration
of Canadian Livestock
Published by authority of the Minister responsible for Statistics Canada.
Minister of Industry, 2001.
All rights reserved. No part of this publication may be reproduced, stored in a retrieval
system or transmitted in any form or by any means, electronic, mechanical, photocopying,
recording or otherwise without prior written permission from Licence Services, Marketing
Division, Statistics Canada, Ottawa, Ontario, Canada K1A 0T6.
April 2001
Catalogue No. 21-601-MIE01047
Frequency: Occasional
Ottawa
La version française est disponible sur demande (no 21-601-MIF01047 au catalogue)
_____________________________________________________________________
Note of appreciation: Canada owes the success of its statistical system to a longstanding
partnership between Statistics Canada and the citizens, businesses and governments of
Canada. Accurate and timely statistical information could not be produced without their
continued co-operation and good will.
Highlights
The total number of livestock farms in Canada has shrunk over time. However, the number of large
farms is on the rise. With large farms come large concentrations of animals and manure in some areas.
This study gives a ‘snapshot’ of where the larger concentrations of livestock and poultry were at the
time of the Census of Agriculture in May 1996. Livestock concentrations (or densities) were analysed in
terms of the total livestock population, irrespective of the different types of animals raised.
The report shows the following:
•
In May 1996, 20% of Canada’s livestock was found in areas with high concentrations of livestock
(high-density areas).
•
Provinces with the most livestock in high-density areas were Quebec, Ontario, Alberta and British
Columbia.
•
In Quebec, British Columbia and Ontario, over 30% of the livestock in each province was in highdensity areas.
•
The largest livestock populations found in high-density areas were beef cattle in Alberta, dairy cattle
and hogs in Quebec, and dairy cattle in Ontario.
•
Livestock concentration is not necessarily linked to large livestock populations. Several high-density
areas appeared to be due to a rather limited amount of livestock associated with an even smaller
farmland base.
More research, using farm-level data and characteristics, is required to determine which type of farms
contributed the most to a greater concentration of livestock in some areas. Further work is required
before concluding whether or not the livestock concentration in certain regions has reached limits where
it could pose an ecological threat.
Catalogue no. 21-601-MIE01047
Table of contents
List of appendices
List of figures
ii
ii
List of tables
ii
List of maps
ii
Introduction and background
Concepts
1
3
Animal units 3
Livestock density on farmland area 3
Census geographical component (CGC)
Density classes 4
Livestock operations 4
Methods, coverage and limitations
Conversion to animal units
GIS methods 5
4
5
5
Centroids 5
Radius 7
Interpolation 8
Data sources and coverage
Limitations 10
9
Inventory versus flow 10
Headquarters rule 10
Census errors 10
Terrain analysis 10
Findings
11
Locations of high concentrations of livestock 11
Types of livestock found in high-density areas 15
Conclusion
17
References
18
Appendices
21
Catalogue no. 21-601-MIE01047
i
List of appendices
A: Definitions 21
B: Regulations, codes of practice and municipal by-laws related to
livestock manure management 22
C: Animal unit coefficients 25
D: Map of proportion of farmland to total land 26
E: Difference between livestock densities based on 20-kilometre radius method and densities based on
enumeration area data 27
F: Regional maps 28
List of figures
1: Distribution of livestock within each density class, by province, May 1996 11
2: Distribution of livestock, by province and density, May 1996 12
3: National distribution of livestock, by livestock type and density, May 1996 15
4: Proportion of livestock in high-density areas, by livestock type and province, May 1996 16
5: Numbers of livestock in high-density areas, by livestock type and province, May 1996 16
List of tables
1: Distribution of livestock, by province and density, May 1996 11
2: High livestock density areas, by sub-basin, May 1996 14
3: Livestock in high-density areas, by livestock type and province, May 1996
15
List of maps
1: Impact of irregular shapes and sizes of enumeration areas on livestock density measurement
2: Impact of selecting centroids inside a standard circle on livestock density measurement 7
3. Impact of the interpolation technique on livestock density display for irregular areas 9
4: Livestock density, Canada, May 1996 13
D1: Map of proportion of farmland to total land 26
F1: Livestock density on farmland, British Columbia 28
F2: Livestock density on farmland, Alberta 29
F3: Livestock density on farmland, Saskatchewan/Manitoba 30
F4: Livestock density on farmland, Ontario 31
F5: Livestock density on farmland, Quebec 32
F6: Livestock density on farmland, Atlantic provinces 33
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ii
Introduction and background
Although the number of farm holdings in Canada is shrinking, the number of large farms is growing.
The decreasing importance of small farms in terms of production and their position in the marketplace is
a long-term trend observed in Canada and in most developed countries.1 Decreasing commodity prices
and cost efficiencies achieved through economies of scale and the adoption of new technologies have
contributed more than anything else to reshaping and redefining the structure of modern agriculture.
It is not yet clear how the industrialization of agriculture has affected Canada’s natural resources such as
soil and water. The perception is that smaller family-run farms represent a lesser threat to human health
and the environment. However, smaller farms are often operating under tight margins, making the
capital investments required for sound environmental and manure management practices difficult. In the
livestock2 industry, large and intensive operations have become a nuisance for some and a symbol of
pride for others. Many people are concerned about the intensification of livestock farms and its possible
impacts on the resource base, particularly on water and air quality.3
Large livestock operations produce large amounts of manure that must be carefully stored, moved and
incorporated into the soil. Manure is a natural fertilizer whose benefits include adding nutrients and
organic matter to the soil and reducing the use of chemical fertilizers. Manure also improves the soil
structure, which in return reduces the risk of erosion, run-off and the infiltration of chemicals, organic
substances or pathogens into surface and ground water. The agronomic and environmental contributions
of manure are well documented.4 However, high concentrations of livestock and the large amounts of
manure they produce are leading many people to wonder whether we can get ‘too much of a good thing’
and whether production systems based on large intensive operations are sustainable in the long term.
Caldwell (1998) notes that the capacity of the soil, ground water and air in a given area to receive
livestock manure is at least partially related to the concentration of livestock in that area.5 However,
these links have yet to be defined.
Some argue that manure management is a non-issue as long as manure is applied on a large land base
and its management is closely monitored. There appears to be a positive correlation between farm size
and the ability to adhere to the recommended management practices—perhaps because large operations
also have the financial resources required to allow them to stay up to date with more stringent
environmental standards and manure management practices. On the other hand, these same larger farms
tend to be more intensive and have higher concentrations of livestock than smaller farms.6
1. For examples of the increasing importance of large livestock farms worldwide, see Janzen et al. (1999), Glenn (1999),
Caldwell (1998) and Fedkiw (1992). As a comparison closer to home, the 1995 Quebec provincial average was 996 pigs per
pig farm, compared with 475 in Ontario, 516 in Denmark and 2,352 in North Carolina (MAPAQ 1999).
2. For simplicity, the term ‘livestock’ is loosely used to include all animal farms, including poultry.
3. For examples, see Toombs (1997, 1998), Fleming et al. (1997), Manitoba Agriculture (2000), Tessier (1998), Mallin
(2000), Stone et al. (1998), Nikiforuk (2000) and Mitchell et al. (2000). Analyses of the risk of nitrogen and phosphorus
contamination are produced in MacDonald (2000a,b), Bolinder et al. (2000) and Eghball and Gilley (1999).
4. For thorough reviews, see Eghball and Power (1994), Choudhary et al. (1996), Haynes and Naidu (1998) and Van Horn
and Hall (1997).
5. Caldwell (1998), p. 104.
6. Schmitt et al. (1996).
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The disposal of manure is an issue, given that manure hauling costs increase with distance. In many
cases, manure must be transported some distance from the source in order to avoid applying it more
heavily than recommended. This can be a real concern in areas where animal populations and densities
are high.7 Land near livestock operations may receive more manure than the soil and plants can use,
while land further away receives none.8 Possible accidents or spills associated with large storage,
hauling and spreading equipment also may present greater environmental risks. These potential
problems could be amplified in areas where farmland adjoining the livestock operations is limited.
Using geographic information systems (GIS) to analyse the concentration of livestock production
expressed in generic animal units, this report focusses on the locations of high concentrations of
livestock and the types of livestock found in these high-density areas. Most other studies have produced
density information for specific types of livestock.9 This report provides maps and research that analyse
livestock densities in terms of the total livestock population, irrespective of the different types of
animals raised.10 Presenting the density of the total livestock population in a particular area is a good
way to evaluate its impact on the environment.
The analysis provides information that will benefit planners, investors, non-governmental organizations,
rural communities and governments interested in expanding livestock production in a sustainable and
responsible manner.
7. Lauwers et al. (1998).
8. Roka and Hoag (1994).
9. For examples, see Marchand and McEwan (1997), Statistics Canada (1994, 1999a, 2000a,b) and CSALE (1996).
10. For examples, see Bernard (1999), GREPA (2000) and Letson and Gollehon (1998).
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Concepts
Animal units
In order to determine livestock density, we used the concept of ‘animal units’ to create equivalence
among different types of livestock, regardless of type, age or end use. This concept is often used in
regulations, codes of practice and municipal by-laws related to livestock production (see Appendix B).
This concept, originally developed in the United States in the 1960s, is based on the number of animals
that would produce the 73 kilograms of nitrogen required to fertilize one acre of corn for one year. The
number of animals of a given kind—such as broiler chickens or beef steers—in one animal unit is
expressed as a coefficient. One cow, for example, equals approximately one animal unit, while four
sows or 125 broiler chickens will be required for one unit. Because of genetic and nutritional
improvements to livestock, these coefficients have been recalculated since they were first developed.
Two methods have been used to estimate the amount of nitrogen produced by animals in a 12-month
period: the Nitrogen Production Method,11 based on average live animal weights; and the Feed
Consumption Method, based on the conversion of feed protein into excreted nitrogen. More recent
research has calculated coefficients based on phosphorus excretion.12 For a number of reasons,
coefficients vary across regions, provinces and countries. The coefficients used in Canada were
reviewed and have proved to be very similar and consistent. (See Appendix C for the coefficients used
in this study.)
Livestock density on farmland area
Livestock density refers to the number of animal units per km2 (100 hectares) of farmland. Farmland
includes all cropland, summerfallow, and improved and unimproved pasture. Land that was not in
agriculture and areas of farms—such as barnyards, laneways, woodlots and marshes13— that were not
suitable for manure disposal were excluded from the calculation. Appendix D presents a map showing
the proportion of farmland to total land.
Livestock density was calculated using the farmland available for spreading manure within a 20kilometre radius of the centre of each enumeration area, the smallest standard geographic area for which
census data are reported.14 The 20-kilometre radius was selected based on two assumptions: it
represented the maximum distance manure could be hauled economically; and no quantity was
transported outside this circle. (For more detail, see Radius under GIS methods.)
To derive the livestock density within each circle, the number of animal units within 20 kilometres of
the centre of each enumeration area was calculated and divided by the farmland area. (See GIS methods
for further details.)
11. For details, see American Society of Agricultural Engineers (1993) and Midwest Plan Service (1985).
12. In some regions, buildup of phosphorus in the soil has become a limiting factor in soil fertilization. See Simard et al.
(1995, 1998, 1999), Bolinder et al. (2000) and Eghball et al. (1996). Because less can be applied, manure must be hauled to a
greater distance (Fleming et al. 1998).
13. Also excluded were farm buildings, gardens, greenhouses, idle land, tree windbreaks, bogs, sloughs, etc.
14. For details, see Statistics Canada. (1999b), pp. 210–212.
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A standard shape, such as the circle around the centre point of each enumeration area, does not appear to
distort the results and the visual display of the values as much as the multitude of irregular shapes
associated with political, administrative or environmental boundaries do. (Map 1 illustrates how
irregular shapes and sizes of the enumeration area could affect the measurement of density.) Moreover,
livestock densities may have little to do with predefined administrative boundaries and areas since
grazing or manure hauling may cross administrative or watershed boundaries, especially in regions
divided into many small administrative areas.
Census geographical component
The census geographical component (CGC) of each farming operation is the geographic area(s) where
the operation is located. An enumeration area may contain several CGCs, depending on the number of
farming operations reported within it.
Agricultural operations may comprise numerous parcels of land in a number of locations. Farm
operators were asked to report on the Census form the location (quarter, section, lot number, township,
concession, meridian, parish and county) of all land owned or leased from others, starting with the farm
headquarters. However, there was no specific question about the exact location of livestock.
In general, livestock reported by a farm were assumed to be kept near the farm’s headquarters. Animal
units were assigned to the enumeration area of the headquarters. This allocation was done regardless of
the location of land holdings in the farm unit. Exceptionally large operations, with land holdings located
in more than one municipality or even province, were divided into parts corresponding to the different
enumeration areas they occupied. This way, we were able to assign the livestock a geographical location
that more closely reflected reality. However, this adjustment affected less than 0.2% of all the livestock.
Density classes
The continuum of livestock density, which can range from 0 to more than 1,000 animal units per km2 of
farmland, is classified into 10 categories.15 In addition to the 0 animal unit per km2 category, this
research has clustered the other nine categories into three broad classes of livestock density: low (0.1 to
3 animal units per km2); medium (between 3 and 80 animal units per km2); and high (over 80 animal
units per km2).
Livestock operations
A livestock operation is a census farm (see definition in Appendix A) that produces at least one of the
following products intended for sale: cattle, pigs, sheep, horses, exotic animals, hens, chickens, turkeys,
exotic birds, milk or cream, eggs, wool, furs and meat.
15. The values of the 10 density classes can be seen in the legends of the maps in Appendix F. The divisions were made
based on statistical distribution. Thresholds for the high-density classes were reported in a number of studies indicating at
which level there is potential risk to the environment. See Paquette (1998) and Schreier and Berka (1999).
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Methods, coverage and limitations
Conversion to animal units
The animal inventory reported by farmers was converted to a common basis, animal units, by
multiplying the inventory for each type and age of livestock by specific coefficients (see Appendix C).
Individual totals were calculated at the enumeration area level for total livestock, cattle (beef and dairy),
pigs, poultry and other livestock. Poultry included birds such as broilers, pullets and pullet chicks, laying
hens and turkeys. Less common birds (such as geese and ducks) and exotic birds (such as ostriches,
game birds and emus) were included in the ‘other’ category.
On the 1996 Census of Agriculture questionnaire, it was not possible to indicate whether calves, heifers
and bulls were beef or dairy. They were allocated as dairy or beef cattle based on historical patterns,
farm types, ratios and provincial supply and disposition tables. This breakdown could be useful in future
studies, as beef and dairy cattle excrete different amounts of nutrient and pathogens.
In the case of turkeys, inventories were reported together without distinction for age or type of
production. Turkey animal unit coefficients were adjusted at the provincial level to compensate for the
predominance of one type of bird, such as broilers versus heavy-weight broilers.
GIS methods
Centroids: In order to build a map, data had to be transformed into a layer of
geographic points,
expressed in terms of longitude and latitude (X, Y) co-ordinates. Since the geographical references
collected or assigned to census farms were the addresses of the headquarters, mapping using these coordinates would raise the issue of confidentiality. Also, the exact location of the field used for pasture or
manure disposal or the barn in which the animals were housed did not necessarily match the location of
the headquarters.
To deal with these issues, different farms were aggregated together inside the boundary of a
geographical area or unit. A few key variables influenced the decision to select a specific geographical
level: if too small, data would need to be suppressed, aggregated to a higher level or merged with close
neighbouring units to protect confidentiality; if too large, the map would lose precision. The scale of the
maps also influenced this decision.
In this study, the enumeration area was chosen as the indicator of the livestock location mainly because
it is the smallest standard geographic area for which census data are reported and it is available for the
whole country.
Enumeration area boundary and size are primarily based on human geography and rivers. It represents
the geographic area canvassed by one census representative. It can cover as much as 440 dwellings in
large urban areas to a minimum of 125 in rural areas. In low population density areas, enumeration areas
are likely to cover more land than in highly populated areas.
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A conventional way to measure livestock density is to take the sum of all animal units inside a particular
enumeration area divided by that enumeration area’s farmland area. This approach has several
limitations associated with the irregularity of the enumeration area shapes and sizes. Unrepresentative
hot spots (high livestock density areas) and cold spots (low livestock density areas) may be induced
simply from the substantial differences in the size of individual enumeration areas.
Artificial hot spots could be produced for farm headquarters located directly beside or near a small town
(which would delineate a small enumeration area). Conversely, artificial cold spots could be created by
the diluting effect on intensive livestock operations of being located in a large enumeration area.
The approach also produces a mosaic display that could be visually very difficult to interpret. As well,
the farming activities of the farm headquarters located inside a particular enumeration area are likely to
transcend the enumeration area boundaries (Map 1).
Map 1: Impact of irregular shapes and sizes of enumeration areas
on livestock density measurement
Number of animal units in each
enumeration area
2
Density (animal units/km of farmland)
Note: Colour changes from light green to dark red as livestock density increases.
Source: Statistics Canada, derived from the 1996 Census of Agriculture.
The first step to reduce this effect was to determine the centroid (centre) of each enumeration area. The
centroid is always located inside the polygon and is usually the centre point of a polygon’s bounding
box (see examples A and B). However, for irregular shapes where the point falls outside the polygon, it
is moved in the shortest horizontal direction required to put it inside the polygon (example C).
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((
A
B
C
Radius: Dealing
with the smallest geographical level available also raised the issue of confidentiality.
The solution to this issue, and to the issue related to irregular shapes and sizes, was to impose a standard
geometric shape—a circle with a 20-kilometre radius—around each centroid. The assumption was that
the loss in precision resulting from this normalization would be offset by the removal of artificial hot
spots or cold spots. Also, since there were more data points inside a circle with a 20-kilometre radius
than inside an individual enumeration area, fewer data would need to be suppressed to protect their
confidentiality.
The density within each circle was then calculated by dividing the total number of animal units for all
centroids falling within the circle by the farmland area within the circle (1,257 km2 for the whole circle
multiplied by the percentage of farmland within it). The calculation was then repeated for each centroid.
Instead of calculating a density value for the enumeration area itself, this approach raised a weighted
average for all centroids that fell inside the same 20-kilometre circle (Map 2 and Appendix E).
Map 2: Impact of selecting centroids inside a standard circle on
livestock density measurement
Densities of selected centroids before
Densities after
Note: Densities are in animal units/km2 of farmland.
Source: Statistics Canada, derived from the 1996 Census of Agriculture.
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A 20-kilometre radius was selected because a number of studies suggested that 20 kilometres was the
farthest that manure could be economically hauled. Farm operators had little incentive to haul manure
beyond the point where transportation was economically viable.16 However, there is no simple method
to calculate the break-even point for transporting manure. It is uneconomical to haul some types of
manure even 4 kilometres. “The two most important factors that determine the net benefit of manure to
farming are the distance the manure has to be hauled and the nutrient content of the manure.”17 Returns
to the livestock operation, input costs such as fuel and fertilizer, crop requirements, landscape, soil
composition and the nutrient content of the manure all influence the maximum distance manure is
transported. Farmers, like other business owners, generally want to maximize profits and consequently
try to minimize their manure handling and transportation costs. The distances that they are prepared to
transport manure may, therefore, not always conform to manure management recommendations.
interpolation technique18 allows the creation of a continuous map with a set of
geographic references (enumeration area centroids). With this technique, new density boundaries appear
between centroids as the relative densities influence each other. A very dense enumeration area impacts
less dense neighbouring enumeration areas; this effect decreases with distance (Map 3).
Interpolation: The
16. Much of the research cited in the literature refers to work done by Freeze and Sommerfeld (1985) and Roka and Hoag
(1994, 1996). In theory, the break-even point and the transportation distance can be higher, but they may change based on the
nutrient and moisture content of the manure. Composted manure can be transported greater distances but not much farm
manure is composted (Janzen 1999). Transport distances can also be greater if there is a regional structure such as the Manure
Management Organization in Quebec to export manure from surplus regions. He and Shi (1998) estimated the maximum
distance to be 4 kilometres with their manure transport model for Michigan.
17. Fleming et al. (1998).
18. Using the inverse distance weighted (IDW) technique (one of several types of interpolation), the value or colour of each
of the pixels in an image (i.e. the points that compose the image) is influenced by each of its surrounding points—an
influence that decreases with distance. A fixed radius of 20 kilometres and an exponent of 2 were used to limit the influence
of surrounding points on the value given to an analysed pixel. For example, a point A located at mid-distance between a point
B and pixel C had four times more weight ([1/(1/2)2]=4) on the final value of pixel C than the point B did. For details, see
ArcView (1996).
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Map 3: Impact of the interpolation technique on livestock density display
for irregular areas
Map without interpolation
Map with interpolation
Note: Colour changes from light green to dark red as livestock density increases.
Source: Statistics Canada, derived from the 1996 Census of Agriculture.
As the livestock population is not evenly distributed across Canada, a major advantage of the chosen
interpolation technique was to assign a value of zero where there was no animal reported inside a 20kilometre circle. In other words, white spots in the maps mean ‘no animals within a 20-kilometre radius
of the centroid’—not a lack of data.
Data sources and coverage
This research uses a data set of Canadian census farms reporting livestock on the 1996 Census of
Agriculture. Farm operators were asked to report inventories of all livestock, including cattle, pigs,
poultry, horses, sheep and lambs, and more exotic animals such as emus, ostriches, elk, deer, bison and
wild boars.
Initially, 184,000 farms were identified. Some records that could not be linked to any areas classified as
agricultural (see the ‘headquarters rule’) were excluded, as were records on farms that did not report
significant numbers of livestock and other records where confidentiality might be compromised if the
data were included. Overall, however, less than 1% of all animal units were excluded from the study.
The data set used for analysis represented 175,000 farms.
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Limitations
Inventory versus flow: Livestock
inventories in mid-May, as reported by farmers on the Census of
Agriculture, do not represent the number of animals that were on the farm during the whole year. The
capacity of the barns, pens or pastures in mid-May is unknown since this information was not elicited on
the 1996 Census of Agriculture questionnaire. No adjustment was made to estimate the average size of
the herd, the total livestock production during the year or the number of livestock in confinement (in
pens, for example) for the whole year or part of the year. The calculated livestock densities refer
specifically to the situation on May 14, 1996.
Headquarters rule: Although the Census of Agriculture data were used at the CGC level, the barns and
livestock may not be as accurately located as they would have been had geographic co-ordinates been
reported on the census questionnaire.
Data originating from a project as large and complex as the Census of Agriculture are
subject to error despite extensive efforts deployed at census time to correct detected undercoverage,
misreporting and data capture errors. The most common types of errors were related to coverage,
missing responses, response errors, and processing errors that were not identified by subsequent checks.
However, the Census of Agriculture had a high response rate and the data were of very good quality.
Census errors:
Terrain analysis: With limited resources available, it was almost impossible to validate the results of
national-level census coverage with field observations. However, to make sure the results were
displayed within a reasonable level of accuracy at the selected scale level, a few maps were validated at
the provincial level with the assistance and local knowledge of provincial agricultural statisticians.
No attempts were made to make adjustment to the spatial distribution of livestock based on physical
geology, geomorphology, hydrology, meteorology, or human settlement patterns and transportation and
communication networks.
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Findings
Locations of high concentrations of livestock
The livestock inventories reported in the 1996 Census of Agriculture were converted into a common
measure, animal units, and mapped to display the spatial distribution and concentration of Canadian
livestock production.
In May 1996, there were 13.4 million animal units in Canada. Alberta had the greatest share of the
national livestock population (34.1%), followed by Ontario (18.7%), Saskatchewan (15.2%), Quebec
(13.8%) and Manitoba (9.5%). The size and location of the cattle industry largely determined these
distributions.
Eight out of 10 farm animals—10.9 million animal units held on 147,000 livestock operations—were
located in medium-density areas, where the concentration of livestock was between 3 and 80 animal
units per km2 of farmland. Two-thirds of this livestock was located in the three Prairie provinces.
Less than one-fifth of all livestock was located in high-density areas, where there was a concentration of
more than 80 animal units per km2 of farmland. Most of the livestock located in high-density areas was
in Quebec, followed by Ontario, Alberta and British Columbia. (Table 1).
Table 1: Distribution of livestock, by province and density, May 1996
B.C.
'000AU %(1)
Alberta
Saskatchew an
'000AU %(1) '000AU %(1)
Manitoba
'000AU %(1)
Ontario
'000AU %(1)
Quebec
Atlantic prov.
'000AU %(1) '000AU %(1)
Canada
'000AU %(2)
Livestock density
Low _less 3 AU/km 2
Medium _3-80 AU/km 2
High _over 80 AU/km 2
Exclusion (3)
5.4
6.1
496.7
4.6
275.2 11.4
8.4 46.7
15.8
4,043.5
499.3
4.2
17.7
37.2
20.7
23.3
60.9
1,977.2
-1.1
68.4
18.2
-6.1
3.8
4.3
1,248.9 11.5
20.1
0.8
1.5
8.3
--1,748.7 16.1
747.4 30.9
1.1
6.1
--1,005.9
9.3
846.9 35.0
---
1.7
340.3
27.6
1.4
1.9
89.1
0.7
3.1 10,861.0 81.1
1.1 2,416.7 18.1
7.8
18.0
--
All densities
785.6
4,562.7 34.1
2,039.5
15.2
1,274.2
2,498.0 18.7
1,853.7 13.8
371.1
2.8 13,384.8
5.9
9.5
100
Notes:
-- too small to be expressed
1. Provincial share of each density class.
2. National share of each density class.
3. No density recorded. Excluded from the map to hide data that could be confidential.
Due to rounding, figures may not add up to totals.
Source: Statistics Canada, derived from the 1996 Census of Agriculture.
Quebec (35.0%) and Ontario (30.9%) together held two-thirds of the livestock in high-density areas.
Alberta (20.7%) had the third largest share (Figure 1).
Figure 1: Distribution of livestock within each density class, by province, May 1996
80
Livestock density
Provincial share (%)
of each density class
70
High (over 80 AU/km2)
Medium (3-80 AU/km2)
Low (less 3 AU/km2)
60
50
40
30
20
10
0
B.C.
Alberta
Saskatchewan
Manitoba
Ontario
Quebec
Atlantic prov.
Source: Statistics Canada, derived from the 1996 Census of Agriculture.
Catalogue no. 21-601-MIE01047
11
Within each province, over 50% of all the livestock was located in medium-density areas. However,
nearly half the livestock in Quebec and around one-third of the livestock in British Columbia and
Ontario was in high-density areas. These areas were predominant where there was a high population of
livestock and/or a relatively low proportion of farmland to total land. (Figure 2).
Figure 2: Distribution of livestock, by province and density, May 1996
4,500
89%
Animal units ('000)
4,000
3,500
3,000
2,500
Livestock density
% of
provincial
total
High (over 80 AU/km2)
Medium (3-80 AU/km2)
Low (less 3 AU/km2)
97%
2,000
70%
1,500
98%
1,000
500
35%
64%
1%
0
B.C.
46%
30%
11%
0%
Alberta
0%
3%
Saskatchewan
54%
92%
2%
0%
Manitoba
0%
Ontario
0%
Quebec
7%
0%
Atlantic prov.
Source: Statistics Canada, derived from the 1996 Census of Agriculture.
From west to east on Map 4, pockets of higher concentration of livestock can be seen in the following
regions: south of the Fraser River in British Columbia; Lethbridge and Newell counties in Alberta; near
Winnipeg in Manitoba; the area north of Waterloo Regional Municipality and parts of Perth, Wellington,
Bruce and Grey counties in southwestern Ontario; and Chutes-de-la-Chaudière, Nouvelle-Beauce, Acton
and Haute-Yamaska in Quebec. (See Appendix F for detailed regional maps.)
Catalogue no. 21-601-MIE01047
12
Map 4: Livestock density, Canada, May 1996
Catalogue no. 21-601-MIE01047
13
Within each province, some clusters or groups of enumeration areas had high densities of livestock.
Sub-provincial livestock concentration was analysed using sub-drainage basin boundaries.19 Table 2
summarizes the data at the sub-basin level for enumeration areas with a high concentration of livestock.
The sub-basins were sorted by decreasing number of total livestock in high-density areas. For example,
the Central St. Lawrence sub-basin contained 5,510 farms, 419 enumeration areas,20 535,592 animal
units, 270,347 animal units of cattle, 170,570 animal units of pigs and 78,463 animal units of poultry, all
located in areas of high livestock density. The highest count in a single enumeration area was 14,700
animal units. The highest number of livestock in a 20-kilometre radius circle around the centroid of one
enumeration area was 115,738 animal units. And the circle with the highest density in this particular
sub-basin had 212.6 animal units per km2.
This table reveals that some hot spots were not necessarily the result of a large number of livestock.
In some areas, a small number of farms with limited livestock may also have high livestock density in
situations where there is a limited amount of farmland available.
Table 2: High livestock density areas, by sub-basin, May 1996
Within an
enum ation
area (EA)
Total
Province
Quebec
Ontario
Ontario
Quebec
Alberta
B.C.
Alberta
Alberta
Ontario
B.C.
Alberta
Manitoba
Atlantic
Ontario
Atlantic
B.C.
Ontario
Alberta
B.C.
Atlantic
B.C.
Atlantic
B.C.
Atlantic
B.C.
Sub-basin
Central St. Law rence
North Lake Erie
East Lake Huron
Low er St. Law rence
Upper South Saskatchew an
Fraser
Red Deer
Battle
Lake Ontario
Thom pson
Bow
Red
Bay of Fundy
East Georgian Bay
Saint John
Upper Peace
Rideau and Low er Ottaw a
Pem bina and Central Athabasca
Upper Fraser
Southeast Atlantic Ocean
Colum bia
Saint John & S.Bay Fundy
Skeena
Gulf St. Law rence & N.Bay Fundy
Knight Inlet & S.Pacific Ocean
535,592
382,090
313,913
309,111
271,048
227,309
117,147
86,632
35,099
30,480
19,106
18,779
11,873
10,469
7,463
6,044
5,747
5,062
3,447
3,362
3,157
1,829
1,798
1,794
1,502
In high livestock density areas
Cattle
Pigs Poultry Farm s EAs
anim al units (AU)
num ber
270,347 170,570 78,463
5,510 419
237,669 89,400 37,793
4,734 143
231,890 40,952 28,527
4,278 118
183,828 98,346 21,428
3,564 191
253,058 10,347
3,592
620
16
126,393 13,407 66,555
3,902 171
102,567
8,454
2,748
634
15
76,759
6,723
229
512
10
13,808
2,150 17,407
522
19
28,050
2
11
91
10
18,131
378
37
112
9
9,105
5,355
3,756
194
7
4,890
1,883
626
154
21
8,352
354
800
224
10
811
560
6,086
37
7
5,270
4
8
38
2
4,786
548
190
69
4
4,441
88
3
84
4
2,974
37
3
62
3
1,143
7
1,722
77
21
2,393
6
7
93
14
1,309
138
288
47
9
1,593
3
3
36
3
1,385
2
360
33
4
1,363
0
0
17
1
Max.
14,700
10,490
9,522
16,771
55,065
8,605
34,529
25,585
5,186
24,496
12,828
4,041
2,618
3,085
5,177
4,841
3,252
3,427
2,089
1,206
860
439
1,566
697
1,502
Within a
20-kilom etre radius
Livestock
anim al units (AU)
Min.
Max.
1
115,738
15
166,733
5
136,139
1
131,804
10
245,133
3
127,544
155
75,448
5
99,110
94
56,891
74
25,047
5
71,906
645
87,164
1
9,322
17
49,118
29
10,357
1,203
4,841
216
47,620
95
13,882
659
2,089
1
5,168
4
2,243
41
7,663
24
1,647
86
3,932
1,502
1,502
Min.
3,309
40,679
31,815
3,194
89,182
61
53,076
62,486
26,354
296
1,310
47,127
1,301
35,087
2,625
1,203
42,470
1,351
659
46
71
374
24
1,969
1,502
Density
(AU/km 2)
Max.
Min.
213
80.2
177
80.6
147
80.3
250
80.4
238
85.5
890
82.0
167
80.2
117
80.3
101
80.1
2,543
81.9
154
87.1
119
83.1
1,167
82.4
88
80.6
551
94.8
251 163.1
86
80.1
201
91.6
124 100.3
569
88.7
1,251
87.4
165
80.6
147
86.8
120
81.2
173 172.5
Note: Includes only enumeration areas with livestock density greater than 80 animal units/km2.
Source: Statistics Canada, derived from the 1996 Census of Agriculture.
The measurements of livestock densities reported here are understated because the method used makes
the assumption that all farmland could be used to spread the manure. In practice, not all farmland can be
fertilized with manure. As well, a farm operator may decide to spread manure on only a portion of the
19. Sub-basins are subsets within river basins or watersheds. Their boundaries follow heights of land and delineate water
surface drainage areas. These physical boundaries, which transcend administrative, political and other types of boundaries,
are more relevant for assessing the potential environmental impact of livestock concentration.
20. A high number of enumeration areas can be expected in highly populated areas.
Catalogue no. 21-601-MIE01047
14
farmland, depending on the cropping system, the hauling distance and the minimum distance from
neighbours or bodies of water. Consequently, the livestock densities reported here might very well be
higher, but it was not possible in this study to identify the area and location of farmland actually used for
manure spreading. Nevertheless, the maps and tables in this report that show animal densities on
farmland are still unique because they provide a good image of the spatial concentration of all farm
animals, regardless of their types.
Types of livestock found in high-density areas
At the national level, in May 1996, almost two-thirds of all livestock was beef cattle (62.6%), followed
by dairy cattle (17.8%), hogs (8.5%), other livestock (6.2%) and poultry (4.9%). Livestock and poultry
are expressed in animal units.
Beef cattle were predominant in Alberta, Saskatchewan and Ontario. As expected, dairy cattle were
predominant in Quebec and Ontario. Hog inventories were largest in Quebec, followed by Ontario,
Manitoba and Alberta. Most poultry stocks were in Ontario and Quebec. Production of ‘other livestock
and poultry,’ including sheep, horses and exotic animals, was predominant in the Prairie provinces
(Table 3).
Table 3: Livestock in high-density areas, by livestock type and province, May 1996
B.C.
'000AU %(1)
Alberta
Saskatchew an
'000AU %(1) '000AU %(1)
Livestock type
Beef cattle
Dairy cattle
Hog
Poultry
Other
438.8
5.2
154.2
6.5
17.3
1.5
84.5 12.8
90.8 10.9
3,851.2 45.9
204.4
8.6
179.0 15.8
62.7
9.5
265.5 31.8
1,754.7
71.3
77.4
23.1
113.1
20.9
3.0
6.8
3.5
13.6
All types
785.6
4,562.7 34.1
2,039.5
15.2
5.9
Manitoba
'000AU %(1)
824.7
9.8
114.1
4.8
179.6 15.9
47.7
7.2
108.2 13.0
1,274.2
9.5
Ontario
'000AU %(1)
982.4
823.9
290.3
238.1
163.5
Quebec
Atlantic prov.
'000AU %(1) '000AU %(1)
Canada
'000AU %(2)
11.7
34.7
25.6
36.1
19.6
395.3
4.7
876.9 36.9
356.3 31.5
154.7 23.5
70.6
8.5
135.4
132.0
33.0
47.9
22.7
1.6
5.6
2.9
7.3
2.7
8,382.4 62.6
2,376.7 17.8
1,132.9
8.5
658.8
4.9
834.5
6.2
2,498.0 18.7
1,853.7 13.8
371.1
2.8 13,384.8
100
Notes:
1. Provincial share of each livestock type.
2. National share of each livestock type.
Due to rounding, figures may not add up to totals.
Source: Statistics Canada, derived from the 1996 Census of Agriculture.
Figure 3 shows, for each livestock type, that a larger share of poultry, hog and dairy animals was found
in high-density areas than in medium-density areas. Hog and poultry production and, to a lesser extent,
dairy production have been associated with enterprises that purchased their feed grains, thus requiring a
relatively small amount of land to operate. Such operations predominate in Central Canada where
proportionately less farmland is available.
Figure 3: National distribution of livestock, by livestock type and density, May 1996
Beef cattle
11%
Dairy cattle
30%
Hog
70%
40%
Poultry
Other
88%
60%
41%
58%
12%
Livestock Density
87%
High (over 80 AU/km2)
Medium (3-80 AU/km2)
Source: Statistics Canada, derived from the 1996 Census of Agriculture.
Catalogue no. 21-601-MIE01047
15
Figure 4 shows the intensity of hog, poultry and dairy production in British Columbia, Quebec and
Ontario, compared with the Prairie provinces and the Atlantic provinces. In British Columbia, more than
three-quarters of the provincial hog and poultry inventories and well over half of all dairy cattle were
concentrated in high-density areas. Quebec and Ontario also had significant proportions of their hog,
poultry and dairy stocks in high-density areas.
Figure 4: Proportion of livestock in high-density areas, by livestock type and province,
May 1996
90
Beef cattle
Dairy cattle
Hog
Poultry
Other
% of provincial total
for each livestock type
80
70
60
50
40
30
20
10
0
B.C.
Alberta
Saskatchewan
Manitoba
Ontario
Quebec
Atlantic prov.
Source: Statistics Canada, derived from the 1996 Census of Agriculture.
Figure 5 presents the inventories (in animal units) of different types of livestock located in high-density
areas and their distribution within each province. The largest livestock populations found in high-density
areas were beef cattle in Alberta, dairy cattle and hogs in Quebec, and beef and dairy cattle in Ontario.
Figure 5: Numbers of livestock in high-density areas, by livestock type and province,
May 1996
500
Beef cattle
Dairy cattle
Hog
Poultry
Other
Animal units ('000)
450
400
350
300
250
200
150
100
50
0
B.C.
Alberta
Saskatchewan
Manitoba
Ontario
Quebec
Atlantic prov.
Source: Statistics Canada, derived from the 1996 Census of Agriculture.
Catalogue no. 21-601-MIE01047
16
Conclusion
The number of livestock farms in Canada is shrinking. However, farming operations are getting larger
and more intensive. With large farms come large concentrations of animals and manure. A first reaction
would be to think that environmental regulations and codes of practices should focus their attention on
large livestock operations.
In order to better understand where the larger concentrations of all livestock and poultry were,
inventories reported in the 1996 Census of Agriculture were converted into a common measure, animal
units, and mapped to display generically the distribution and concentration of Canadian livestock.
Presenting the density of the total livestock and poultry population in a particular area is a good start to
evaluate its impact on the environment. It is the cumulative effect of all types of livestock production
that may affect the environment.
Findings indicate that livestock concentration is not necessarily linked to large livestock populations.
Some high-density areas appeared to be due to a rather limited amount of livestock associated with an
even smaller farmland base. Certainly this situation is a factor limiting production expansion. Analysing
concentrations of all livestock present on all farms, regardless of the size of the farm and the type of
animals, is the best way to get the whole picture.
This study cannot conclude whether or not large livestock farms contributed the most to a greater
concentration of livestock in some areas. Exploring this would require further work to link livestock
densities with farm level data and characteristics—such as type of farm, operating arrangements and
farm size.
Additional research would be required before concluding whether or not the livestock concentration in
certain regions had reached limits where it could pose an ecological threat. It would require establishing
local or regional nutrient budgets based on amount of manure produced, farmland available for manure
disposal, soil characteristics, crop requirements, and use of chemical fertilizer and municipal sewage
sludge. This could help identify areas where the environment might be at risk from a lack of sufficient
land to recycle animal waste.
Catalogue no. 21-601-MIE01047
17
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Appendix A
Definitions
Census consolidated subdivision (CCS)
A census consolidated subdivision is a grouping of census subdivisions (see below). Generally the
smaller, more urban census subdivisions, such as towns and villages, are combined with the surrounding
larger, more rural census subdivision, in order to create a geographic level between the census
subdivision and the census division.21
Census division (CD)
Census division is the general term applied to intermediate geographic areas established by provincial
law between the municipality (census subdivision) and the provincial levels. Census divisions represent
counties, regional districts, regional municipalities and other types of provincially legislated areas.22
Census farm
A census farm is an agricultural operation that produces at least one of the following products intended
for sale: crops (field crops, tree fruits or nuts, berries or grapes, vegetables, seed); livestock (cattle, pigs,
sheep, horses, exotic animals, etc.); poultry (hens, chickens, turkeys, exotic birds, etc.); animal products
(milk or cream, eggs, wool, furs, meat); or other agricultural products (greenhouse or nursery products,
Christmas trees, mushrooms, sod, honey, maple syrup products).
The definition of a census farm was expanded in 1996 to include commercial poultry hatcheries and
operations that produce only Christmas trees.23
Census of Agriculture
The Census of Agriculture, conducted every five years, produces a snapshot of Canadian agriculture by
providing statistics at national, provincial and sub-provincial levels on crop areas, number of livestock,
number and value of farm machines, farm operating expenses and receipts, purchase of capital assets,
weeks of paid labour, and land management practices.24 The 1996 Census of Agriculture was conducted
on May 14, 1996.
Census subdivision (CSD)
Census subdivision is the general term applied to municipalities (as determined by provincial
legislation) or their equivalent (for example, Indian reserves, Indian settlements and unorganized
territories).25
21. For details, see Statistics Canada (1999b), pp. 178–180.
22. For details, see Statistics Canada (1999b), pp. 180–182.
23. For details, see Statistics Canada (1997), p. xxxi.
24. For details, see Statistics Canada (1999b), pp. 178–180.
25. For details, see Statistics Canada (1999b), pp. 195–197.
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Confidentiality
The Statistics Act requires that all census information be kept confidential. No person or institution
outside Statistics Canada (including other government departments and agencies, the courts and the
RCMP) can access census information provided by individual respondents. For this study, all tabulated
data and maps were subject to confidentiality restrictions. A series of computerized checks was
performed to suppress data that could result in the disclosure of information concerning a particular
agricultural operation or individual. Any area with a 20-kilometre radius that contained very few farms
was not displayed separately, but was simply suppressed from the maps.
Enumeration area
An enumeration area is the geographic area canvassed by one census representative. It is the smallest
standard geographic area for which census data are reported. Canada’s entire surface area is divided into
enumeration areas.26
26. For details, see Statistics Canada (1999b), pp. 210-212.
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Appendix B
Regulations, codes of practice and municipal by-laws related to livestock
manure management27
Nova Scotia Department of Agriculture and Marketing, Nova Scotia Department of the Environment.
1997. Environmental Regulations Handbook for Nova Scotia Agriculture.
<http://agri.gov.ns.ca/rs/envman/educate/handbook.htm#sheet8>. (Accessed March 2001)
Nova Scotia, examples of land use by-laws:
• Eastern Antigonish County Planning Area. 1994.
<http://www.munisource.org/antigonish/lub-east.htm>. (Accessed March 2001)
• Rural Cape Breton District Planning Commission, Isle Madame, Cape Breton, County of
Richmond. 1998. <http://www.rcbplan.ns.ca/isle_madamelub.htm>. (Accessed March 2001)
New Brunswick. 1999. New Livestock Operations Act proclaimed.
<http://www.gnb.ca/cnbnews/afa/1999e0585ag.htm>. (Accessed March 2001)
New Brunswick Agriculture and Rural Development. 1997. Manure Management Guidelines for New
Brunswick. <http://www.gnb.ca/afa-apa/20/10/2010005e.htm>. (Accessed March 2001)
Quebec Ministry of the Environment. 1998. Reduction of pollution from agricultural sources.
<http://www.menv.gouv.qc.ca/sol/agricole-en/>. (Accessed March 2001)
Ontario Ministry of Agriculture, Food and Rural Affairs (OMAFRA). 1996. Land Application of Liquid
Manure in an Environmentally Responsible Manner. Fact Sheet (Don Hilborn.)
<http://www.gov.on.ca/OMAFRA/english/livestock/dairy/facts/92-164.htm>.
(Accessed March 2001)
_______. 2000. Proposed Standards for Agricultural Operations In Ontario.
<http://www.gov.on.ca/OMAFRA/english/agops/index.html>. (Accessed March 2001)
Ontario, examples of nutrient management by-laws:
• Oxford County. 1999.
<http://www.county.oxford.on.ca/general/newitems/nutrientmanagement.htm>. (Accessed
March 2001)
• The Corporation of the Township of West Nissouri, Middlesex County. 1999.
<http://www.twp.west-nissouri.on.ca/Bylaw17-99.htm>. (Accessed September 2000)
• Perth County. <http://www.countyofperth.on.ca/depts/bylaws/bl2573.html>. (Accessed
March 2001)
• County of Brant. <http://www.county.brant.on.ca/bylaws/bl00-121.htm>. (Accessed March
2001)
27. This is not a complete list.
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Ontario Federation of Agriculture. The Ontario Farm Environmental Coalition’s Nutrient Management
Planning Strategy.
<http://www.ofa.on.ca/aglibrary/Research/Nutrient%20Management%20Planning%20Strategy/d
efault.htm>. (Accessed March 2001)
Manitoba Regulations and Approval Processes.
• Manitoba Regulations and Guidelines.
<http://www.gov.mb.ca/agriculture/news/lsteward/stewardship7.html>. (Accessed March
2001)
• Regulatory Approaches Throughout North America.
<http://www.gov.mb.ca/agriculture/news/lsteward/stewardship8.html>. (Accessed March
2001)
• Manitoba Livestock Manure and Mortalities Management Regulation under the
Environment Act. <http://www.gov.mb.ca/chc/statpub/free/pdf/e125.pdf>.
(Accessed March 2001)
• Farm Practices Guidelines for Hog Producers in Manitoba.
<http://www.gov.mb.ca/agriculture/livestock/pork/swine/bah00s00.html>. (Accessed March
2001)
Saskatchewan. 1995. The Agricultural Operations Act.
<http://www.qp.gov.sk.ca/orphan/legislation/a12-1.htm>. (Accessed March 2001)
Saskatchewan Agriculture and Food.
• Intensive Livestock Operations Guide of Recommended Practice.
• Managing Manure as a Fertilizer for Prairie Agriculture.
<http://www.agr.gov.sk.ca/DOCS/livestock/pork/manure_management/managingmanure.
asp>. (Accessed March 2001)
Alberta Agriculture, Food and Rural Development.
• Regulatory Options for Livestock Operations.
<http://www.agric.gov.ab.ca/archive/ilo/index.html>. (Accessed March 2001)
• Regulation of Intensive Livestock Elsewhere in North America.
<http://www.agric.gov.ab.ca/archive/ilo/section4d.html>. (Accessed March 2001)
• 2000 Code of Practice for Responsible Livestock Development and Manure Management.
<http://www.agric.gov.ab.ca/agdex/400/400_27-2.html>. (Accessed March 2001)
• Proposed Act for Intensive Livestock Operations.
<http://www.agric.gov.ab.ca/economic/policy/ilo/ilo_act.html>. (Accessed March 2001)
British Columbia. 1992. Agricultural Waste Control Regulation Waste Management Act, Health Act.
<http://www.qp.gov.bc.ca/stat_reg/regs/elp/r131_92.htm>. (Accessed March 2001)
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Appendix C—Animal unit coefficients
1
Selected
coefficients
Poultry
Broilers/roasters
Pullets
Laying hens
Turkeys
Duck
Geese
Other
Cattle
Dairy cow s
Dairy heifers
Dairy calves
Dairy bulls
Beef cow s
Beef heifers
Beef Bulls
Beef steers
Beef calves
N.S.
200
1000 b
300
300 b
120
125
71 100-300 b
2
4
Sk.
Ab.
240
505
144
61-159
250
250
125
55-100
250
200
500
125
50-100
100
170
300
100
70-120
200
200
300
120
30-100
50
50
50
0.8
1a
2b
1
2b
1.1
1.7
5.1
6.5
23
5
5
8
30
4a
15 b
Sheep & lambs
Rams
Ew es & w ethers
Lambs
7
5
16
4a
7
Mb.
40 b
Pigs
Boars
Sow s
Other over 45 lbs.
Other under 45 lbs.
6
On.
100
1a
5
Qc.
50
50
0.75
1
3.3
0.75
1
1.4
1
1.3
4.4
3
N.B.
1.7
4.6 a
1
2
5
1
1
2
1
2
5
3
4
5
25
4
12-25
100
50
50
50
130
1a
2
3-6
0.83
1.25-2.2
1
2
1
1.5
4
0.75
1
3.3
0.75
1
1.3-1.6
1
1.3
4.4
5
5
4
20
5.5
3-4
7
50
3
3
4-6
20
5
5
5-11
30
4a
10
5
5b
10
7
7
14
7
7
16
1
2
0.5 b
2
8
B.C.
Other
Horses
0.75
1
1
1a
0.75
1
0.75 a
Goats
7
4.6
6
4-10
7
7
Rabbits
40
40 a
40
40
40 a
Mink
80
100 a
80
100
80 a
Foxes
40
40
40
40 a
Bisons
1
1
1
1
Deers
8
8
8
Llamas
Ostriches
7
3
7
Emus
16
10
5
16
Wild boars
4
5
4
Elks
5
5
1.9
Notes:
a. Includes offspring, calf, litter, kits or associated males.
b. Marketed during a year.
Sources:
1. Nova Scotia Department of Agriculture and Marketing, Nova Scotia Department of the Environment, 1997, Environmental Regulations
Handbook for Nova Scotia Agriculture.
2. Number of animals to produce 110 kg N/ha. New Brunswick Agriculture and Rural Development, 1997 Manure Management Guidelines
for New Brunswick.
3. GREPA, 2000. Le portrait agroenvironnemental des fermes du Québec.
4. Based on OMAFRA standards include in many municipal by-laws. Also in Ontario Federation of Agriculture. 1998. The Ontario Farm
Environmental Coalition’s Nutrient Management Planning Strategy.
5. Manitoba Agriculture and Food, Appendix 1 in Farm Practices Guidelines for Hog Producers in Manitoba.
6. Saskatchewan Agriculture and Food, Guidelines for Establishing and Managing Livestock Operations.
7. Alberta Agriculture, Food and Rural Development , Proposed Regulations for Intensive Livestock Operations.
8. Combination of livestock equivalent to 455 kg. B.C. Agricultural Waste Control Regulation Waste Management Act.
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Appendix D Map D1: Proportion of farmland over total land
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Appendix E
Figure E1: Difference between livestock densities based on 20kilometre radius method and densities based on enumeration area
data
Notes:
Excludes extreme values (differences above 1000 or less than –1000 animal units/km2).
Overall, the 20 kilometre-radius method lowered density values (lower mean compared with mean value of densities calculated with
enumeration area data).
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Appendix F – Regional maps
Map F1: Livestock density on farmland, British Columbia
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Map F2: Livestock density on farmland, Alberta
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Map F3: Livestock density on farmland, Manitoba and Saskatchewan
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Map F4: Livestock density on farmland, Ontario
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Map F5: Livestock density on farmland, Quebec
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Map F6: Livestock density on farmland, Atlantic provinces
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